Sistem Pengolahan Sinyal Pernapasan Menggunakan Radar Continuous Wave Sebagai Indikator Kebugaran Jasmani

Pandya, Nayaka Dzaky (2026) Sistem Pengolahan Sinyal Pernapasan Menggunakan Radar Continuous Wave Sebagai Indikator Kebugaran Jasmani. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5023221045-Undergraduate_Thesis.pdf Restricted to Repository staff only Download (13MB) | Request a copy

Abstract

Pemantauan kebugaran jasmani secara konvensional umumnya mengandalkan pengukuran parameter kardiovaskular seperti laju jantung, sementara parameter pernapasan yang juga memiliki korelasi kuat dengan kapasitas aerobik belum banyak dimanfaatkan secara optimal, khususnya melalui metode pengukuran nirkontak. Penelitian ini mengembangkan sistem pengolahan sinyal pernapasan berbasis radar Continuous Wave (CW) sebagai indikator kebugaran jasmani yang mampu mengakuisisi dan menganalisis sinyal pernapasan manusia tanpa kontak fisik. Sistem yang dibangun mengintegrasikan modul radar K-MC1 (RFbeam) pada frekuensi 24 GHz, mikrokontroler STM32H7S3L8 sebagai unit demodulasi fasa perangkat keras menggunakan metode arctangent demodulation, dan perangkat lunak berbasis Python dengan antarmuka grafis untuk akuisisi real-time, pemrosesan sinyal, serta analisis kebugaran. Pipeline pemrosesan sinyal mencakup high-pass filter, normalisasi, moving average, dan bandpass filter untuk mengisolasi komponen frekuensi pernapasan, dilanjutkan dengan ekstraksi parameter meliputi laju pernapasan istirahat, I/E ratio, waktu pemulihan pernapasan pasca latihan (T_{rec}), dan rasio amplitudo napas yang diintegrasikan dalam sistem penilaian kebugaran berbasis weighted scoring dengan bobot RR 30%, T_{rec} 40%, I/E ratio 15%, dan A_{ratio} 15%. Pengujian dilakukan terhadap 12 subjek yang terdiri dari 6 kelompok terlatih dan 6 kelompok tidak terlatih dengan protokol tiga fase: baseline 120 detik posisi duduk, intervensi treadmill 12 menit, dan recovery 300 detik posisi berdiri. Validasi terhadap respiratory belt menghasilkan korelasi Pearson rata-rata 0,703 pada fase baseline dan 0,509 pada fase recovery, dengan MAE breathing rate rata-rata 1,81 bpm pada baseline dan 4,83 bpm pada recovery. Sistem weighted scoring berhasil mengklasifikasikan kebugaran seluruh subjek dengan hasil yang secara umum konsisten, di mana kelompok terlatih dominan pada kategori "Bugar" hingga "Sangat Bugar" sementara kelompok tidak terlatih dominan pada kategori "Cukup Bugar", menunjukkan bahwa radar CW berpotensi digunakan sebagai sensor pernapasan nirkontak yang fungsional untuk aplikasi penilaian kebugaran jasmani dalam kondisi laboratorium terkontrol.
==================================================================================================================================
Conventional physical fitness monitoring generally relies on cardiovascular parameters such as heart rate, while respiratory parameters that also have strong correlations with aerobic capacity have not been widely utilized, particularly through non-contact measurement methods. This research develops a respiratory signal processing system based on Continuous Wave (CW) radar as a physical fitness indicator, capable of acquiring and analyzing human respiratory signals without physical contact. The system integrates a K-MC1 radar module (RFbeam) operating at 24 GHz, an STM32H7S3L8 microcontroller as a hardware phase demodulation unit using arctangent demodulation, and Python-based software with a graphical interface for real-time acquisition, signal processing, and fitness analysis. The signal processing pipeline includes a high-pass filter, normalization, moving average, and bandpass filter to isolate respiratory frequency components, followed by parameter extraction covering resting respiratory rate, I/E ratio, post-exercise respiratory recovery time (T_{rec}), and breathing amplitude ratio, which are integrated into a weighted scoring fitness assessment system with weights of 30% for RR, 40% for T_{rec}, 15% for I/E ratio, and 15% for A-ratio. Validation was conducted on 12 subjects consisting of 6 trained and 6 untrained individuals using a three-phase protocol: 120-second seated baseline, 12-minute treadmill intervention, and 300-second standing recovery. Validation against a Vernier respiratory belt yielded an average Pearson correlation of 0.703 during baseline and 0.509 during recovery, with average breathing rate MAE of 1.81 bpm during baseline and 4.83 bpm during recovery. The weighted scoring system successfully classified fitness levels for all subjects in a manner generally consistent with the trained and untrained groupings, where the trained group dominated the "Fit" to "Very Fit" categories while the untrained group predominantly fell under "Moderately Fit", demonstrating that low-cost commercial CW radar has the potential to serve as a functional non-contact respiratory sensor for physical fitness assessment applications in controlled laboratory conditions.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	radar continuous wave, sinyal pernapasan, kebugaran jasmani, arctangent demodulation, weighted scoring, laju pernapasan, waktu pemulihan pernapasan, continuous wave radar, respiratory signal, physical fitness, arctangent demodulation, weighted scoring, respiratory rate, respiratory recovery time
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.9 Signal processing.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Nayaka Dzaky Pandya
Date Deposited:	30 Jul 2026 01:52
Last Modified:	30 Jul 2026 01:52
URI:	http://repository.its.ac.id/id/eprint/134963

Actions (login required)

View Item